Blind multichannel system identification with applications in speech signal processing

We are presenting a new approach for blind multichannel system identification. The approach relies on the existence of so called exclusive activity periods (EAPs) in the source signals. EAPs are time intervals during which only one source is active and all other sources are inactive (i.e. zero). The existence of EAPs is not guaranteed for arbitrary signal classes. EAPs occur very frequently, however, in recordings of conversational speech. The methods proposed in this paper show how EAPs can be exploited to improve the performance of blind multichannel system identification systems in speech processing applications. We have shown that for modestly complex tasks the proposed method achieves an improvement of over 10 dB in signal-to-interference ratio over conventional techniques.